Unseen threat: how subclinical atherosclerosis increases mortality risk in patients with type 1 diabetes.

Background: Cardiovascular disease (CVD), particularly ischemic heart disease, remains the leading cause of death and morbidity in patients with type 1 diabetes. Detecting subclinical atherosclerosis could enhance cardiovascular risk stratification and enable individualised therapies. The aim of this study is to investigate the prevalence and predictors of subclinical atherosclerosis in patients with type 1 diabetes without overt cardiovascular disease (CVD) and to assess its impact on patient survival over a follow-up period of at least 5 years.

Methods: This observational study included 507 patients treated at the Diabetes Unit of the Hospital of Girona Doctor Josep Trueta between 2015 and 2023. The inclusion criteria for patients were as follows: those aged 18 and older with diabetes for a minimum of 10 years or those aged 40 and older with a diabetes for at least 5 years. Subclinical atherosclerosis was identified via ultrasound imaging of the carotid and femoral arteries. Clinical and biochemical evaluations were also conducted. Major cardiovascular events (MACE) and deaths from other causes were monitored, and survival analysis was performed using Kaplan‒Meier methods.

Results: Subclinical atherosclerosis was detected in 218 patients (43%). Multivariate analysis revealed that the male sex, diabetic nephropathy, tobacco exposure, higher HbA1c levels, older age, and longer diabetes duration were significant predictors. During a mean follow-up of 70.64 ± 27.08 months, 19 patients experienced MACE, and 13 died from any cause. The probability of MACE or death was greater in patients with subclinical atherosclerosis, with a hazard ratio (HR) of 25.1 (95% CI 5.81-108, p < 0.001) for MACE and an odds ratio (OR) of 7.57 (95% CI 1.97-53.9, p = 0.004) for death.

Conclusion: Subclinical atherosclerosis is independently associated with increased overall mortality and MACE in patients with type 1 diabetes. Identifying clinical predictors can improve risk stratification and personalised therapeutic strategies to prevent MACEs in this high-risk population.